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El monitoreo del contenido de humedad en el suelo es especialmente importante, ya que proporciona información relevante para tomar decisiones acertadas, en cuanto a riego, fertirriego y manejo del estrés hídrico. Este trabajo tiene como objetivo validar un modelo de estimación del contenido de agua en el suelo, mediante espectroscopía de reflectancia difusa en el rango del infrarrojo cercano. Los suelos evaluados provienen de los municipios de Puerto Gaitán (Meta), Espinal (Tolima) y Mosquera (Cundinamarca). En los dos primeros se establecieron redes rígidas, para seleccionar los puntos de muestreo y empleando dos profundidades en cada caso (0-10 y 10-30; 0-10 y 10-25 cm, respectivamente). Para el tercero, se describieron 77 calicatas y se tomaron muestras a 0-10 y 10-35 cm de profundidad. Posteriormente, se evaluó el contenido de humedad considerando 0, 15 y 30 % de humedad. Los datos obtenidos se analizaron con estadística descriptiva. Se empleó la validación cruzada y externa para cada modelo y se obtuvo un modelo general, a partir de los datos de los tres sitios. Los modelos obtenidos para cada sitio de muestreo y el modelo general tienen buena capacidad predictiva. Según los resultados, se afirma que la espectroscopía de reflectancia difusa NIR es una excelente opción para determinar el contenido de agua en el suelo. De igual manera, a partir del análisis de componentes principales, se identificó una diferenciación entre contenidos de agua de los suelos estudiados.
Monitoring soil moisture content is especially important as it provides relevant information for making informed decisions regarding irrigation, fertigation, and water stress management. This study aims to validate a model for estimating soil water content using diffuse reflectance spectroscopy in the near-infrared range. The evaluated soils come from the municipalities of Puerto Gaitán (Meta), Espinal (Tolima), and Mosquera (Cundinamarca). In the first two municipalities, rigid networks were established to select sampling points, with two depths considered for each case (0-10 and 10-30 cm; 0-10 and 10-25 cm, respectively). For the third municipality, 77 soil pits were described, and samples were taken at depths of 0-10 and 10-35 cm. Subsequently, moisture content was evaluated at 0, 15, and 30 % moisture levels. The obtained data were analyzed using descriptive statistics. Cross-validation and external validation were applied to each model, and a general model was developed based on the data from all three sites. The obtained models for each sampling site and the general model demonstrated good predictive capacity. Based on the results, it is affirmed that near-infrared diffuse reflectance spectroscopy is an excellent option for determining soil water content. Similarly, principal component analysis identified differentiation between water contents of the studied soils.
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ABSTRACT: Vis-NIR-SWIR reflectance spectra of leaf samples, collected in the laboratory, allow the calibration of predictive models to quantify their physicochemical attributes in a practical manner and without producing chemical residues. This technique should enable the development of management strategies for intensification of pasture use. However, spectral analysis performed in the laboratory may be affected by the deterioration of plant material during transport from the field to the lab, so storage methods are necessary. This research aimed to evaluate the effects of different storage methods on the spectral response of Mombasa grass leaves. Three methods were evaluated: (i) artificially refrigerated environment, (ii) humid environment, and (iii) without microenvironment control. These methods were tested in five different storage times: 2 hours, 4 hours, 8 hours, 24 hours and 48 hours. The spectral behavior of the leaves still inserted in the plant was used as a quality reference. Results showed notable changes at the earliest storage time for the treatment without microenvironment control. Both methods with microenvironment control stabilized the occurrence of spectral changes over 48 hours of the samples storage, thus both were suggested for this species.
RESUMO: Espectros de reflectância vis-NIR-SWIR de amostras foliares, coletados em laboratório, permitem a calibração de modelos preditivos para quantificação de seus atributos físico-químicos de maneira prática e sem produção de resíduos químicos. Esta técnica permite o desenvolvimento de estratégias de manejo para a intensificação do uso de pastagens. Contudo, análises espectrais realizadas em laboratório podem ser afetadas pela deterioração do material vegetal durante o transporte do campo ao laboratório, fazendo-se necessário a utilização de métodos de armazenamento. O presente trabalho objetivou avaliar o efeito de diferentes métodos de armazenamento na resposta espectral de folhas de capim Mombaça. Avaliou-se três métodos: (i) ambiente refrigerado artificialmente; (ii) ambiente úmido; e (iii) ao ar livre, sem controle do microambiente; assim como, cinco diferentes tempos de armazenamento: 2 horas, 4 horas, 8 horas, 24 horas e 48 horas. O comportamento espectral das folhas ainda inseridas na planta foi utilizado como referência de qualidade. Os resultados mostraram alterações pronunciadas para o armazenamento ao ar livre já nos primeiros intervalos de tempo. Ambos métodos com controle de microambiente permitiram estabilizar a ocorrência de alterações espectrais ao longo das 48h de armazenamento das amostras, sendo ambos sugeridos para esta espécie.
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Objective: To establish a near-infrared diffuse reflectance spectroscopy(NIRS) identification model for crude products,counterfeit products and processed products of Calamina by principal component analysis(PCA) and support vector machine(SVM) algorithm. Method: NIRS of crude products,counterfeit products and processed products of Calamina were collected,the characteristic spectrum segments were selected,the preprocessing method and the optimum principal component number were optimized,and the PCA-SVM qualitative model was established. Result: The characteristic spectrum segment of analysis model was 7 500-4 000 cm-1.Spectra were preprocessed by the first-order derivative method(FD).The optimum principal component number was 5. And the optimum internal parameters of SVM[penalty factor(c)=0.25 and kernel function parameter(g)=8] were screened by applying the grid search algorithm.In the PCA-SVM qualitative model,the prediction accuracy rate was 100%for the 5-fold cross validation,and the prediction accuracy rates also were 100%both for training set and test set. Conclusion: PCA-SVM analysis model of NIRS for Calamina samples has a high prediction accuracy rate,and it can be used for the rapid and nondestructive identification of crude products,counterfeit products and processed products of Calamina by combining the diffuse reflection technique on solid powder.
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Cervical cancer is a common female malignant tumor. It has been increasing and rejuvenating in recent years. Early screening of cervical cancer is an effective control method to block cancer. In this study, a diffuse reflectance spectrum detection and analysis system based on LabWindows development software and MariaDB database was developed, which can acquire and save the spectral data to the database. The method of a neural network model based on spectral database was built to distinguish the cervical tissue and the normal tissue. The nude mouse tumor model test and human volunteer test were performed respectively, which verified that the system can distinguish between normal tissue and tumor tissue, and can be applied to the screening of cervical precancerous lesions.
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Animals , Female , Humans , Mice , Mice, Nude , Neural Networks, Computer , Spectrum Analysis , Uterine Cervical Neoplasms , Diagnostic ImagingABSTRACT
A printed polymer for selective identification of levofloxacin was synthesized on the surface of silica gel with levofloxacin as template molecule. The polymer was characterized by elemental analysis and infrared spectroscopy, and the properties of the polymer were determined by dynamic adsorption and selective adsorption. The results showed that the maximum adsorption capacity of the imprinted polymer was 56.33 mg/g and the imprinting factor was 2.62. The imprinted polymer was applied to quantitative analysis of levofloxacin with molecular imprinted solid phase extraction spectroscopy (SPES). The SPES was carried out in an elaborately designed device with which the interested analyte was extracted by the solid phase extraction medium and the diffuse reflectance spectrum was measured directly on the solid medium without elution. SPES has simplified the operation process and improved the sensitivity. The regression equation of the standard curve was A=0. 0496C+0. 2412, the correlation coefficient (R2) was 0. 9924, the linear range was 0. 25-9.0 mg/L,and the detection limit was 0.24 mg/L. The recoveries of determination of levofloxacin in Pork samples were 89.1%-92.0%, and the relative standard deviations (RSDs) of the three parallel tests were 3.4%-7.9%. Compared with the traditional enrichment and separation technique, this method developed here had some advantages such as miniaturization and integration, high sensitivity and selectivity, low cost, simple operation and rapid detection.
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Objective: To develop a model for rapid and non-destructive determination of amoxilcillin sodium and sulbactam sodium for injection using the analysis of near infrared diffuse reflectance spectroscopy (NIR) and chemometrics.Methods: Totally 41 batches of commercial samples and 20 batches of laboratory samples were analyzed by NIR and the legal methods.The first derivative and vector normalization were selected as the preprocessing methods and 8 720-5 446 cm-1 was selected as the frequency range.Results: The quantitative model was constructed based on 16 batches of commercial samples and 15 batches of laboratory samples (0.75 g) and the content ranged from 4.45% to 61.82% for amoxilcillin and 15.75% to 30.25% for sulbactam.The root mean square errors of cross validation (RMSECV), determination coefficients (R 2) and root mean square errors of prediction (RMSEP) respectively was 0.858 , 0.998 1 and 0.936 for amoxilcillin, and respectively was 0.541 , 0.988 1 and 0.423 for sulbactam.The model was tested based on 5 batches of commercial samples and 5 batches of laboratory samples (0.75 g) and the results well met with those of the legal methods with difference ≤ 1.5 %.The model also applied in 10 batches of commercial samples (1.5 g) and 2 batches of samples from the other manufacturers.Conclusion: The non-destructive quantitative NIR methods are accurate with good reproducibility, and applicable for the rapid analysis of amoxilcillin sodium and sulbactam sodium for injection.
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OBJECTIVE:To establish the method for rapid determination of nuezhenoside in Salvia miltiorrhiza.METHODS:The contents of salvianolic acid B,rosmarinic acid,lithospermic acid and tanshinone (tanshinone Ⅱ A+tanshinone Ⅰ +cryptotanshinone) were determined by HPLC (as reference value).Quantitative model for the contents of above components was established by partial least square (PLS)-NIR spectra.According to the reference value,143 samples were collected and the spectrum was pretreated by first-order derivative.The optimal range of wave band for salvianolic acid B,rosmarinic acid,oxalic acid and tanshinone were 6 773.98-3 981.12,6 670.85-3 996.54,8 544.66-3 936.28,8 188.06-3 875.31 cm-1.RESULTS:The methodology for the content determination of salvianolic acid B,rosmarinic acid,oxalic acid and tanshinone were in line with the requirement.The coefficient (R2) of internal cross validation for quantitative correction model of salvianolic acid B,rosmarinic acid,oxalic acid and tanshinone were 0.919 0,0.832 2,0.821 5,0.925 6.The deviation of corrected mean square roots were 4.46,0.48,1.34,0.71,respectively.The R2 values of external validation were 0.852 6,0.957 3,0.819 3,0.953 1,respectively;and mean square root of prediction error (RMSEP)were 9.77,0.28,0.94,0.63,respectively.CONCLUSIONS:The method is rapid,accurate,simple and pollution-free,and can be used for rapid determination of multi-maker ingredients in S.miltiorrhiza.
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OBJECTIVE: To establish a nondestructive and rapid analysis method to measure the critical parameter, mixing uniformity, in the production of Ginkgo leaf dispersible tablets in order to control the quality of products. METHODS: The near-infrared diffuse reflectance spectroscopy (NIRDRS) spectra of the pre-mix and the total mixed Ginkgo leaf dispersible tablets (Wuhan Jianmin Suizhou Pharmaceutical Co., Ltd.) were obtained. The mixing uniformity of samples was monitored by quantitative analysis model and standard deviation method combined with the Mahalanobis distance method, respectively. Meanwhile, lab-made mixing samples and dynamic simulation mixing process were used to validate the feasibility of Mahalanobis distance method. RESULTS: The results obtained from quantitative analysis model and standard deviation method were consistent with each other, and the Mahalanobis distance method was feasible for monitoring the mixing process. CONCLUSION: The method is rapid, simple, and can be used for online and sideline analysis in drug production process.
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This study was aimed to establish a qualitative model of near-infrared spectroscopy in order to accurately and rapidly identify several mineral Chinese medicinals from fossil including Os Draconis, Dens Draconis, Fossil Shell of Spirifer, and Fossil Crabs. The near-infrared diffuse reflectance spectroscopy combined with OPUS software was used to analyze the spectral characteristics of these samples. The pattern recognition method was explored through cluster analysis. And the accuracy of the model was verified. The results showed that these mineral Chinese medicinals from fossil had their characteristics absorption so that they can be quickly and accurately differentiated from each other through pattern recognition method. It was concluded that based on near-infrared spectroscopic mod-eling, these mineral Chinese medicinals from fossil including Os Draconis, Dens Draconis, Fossil Shell of Spirifer, and Fossil Crabs can be quickly and accurately identified.
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OBJECTIVE: To develop a method for rapid determination of proanthocyanidins and total phenolics in the seedpod of Nelumbo nucifera Gaertn by near infrared diffuse reflectance spectroscopy. METHODS: Calibration models were established using PLS (partial least squares) method, while the contents of proanthocyanidins and total phenolics were measured by UV. RESULTS: The range of 7500-6900 cm-1 of near infrared spectra was selected. Different spectra pretreatment methods were compared, and it was shown that second derivative pretreatment and Savitzky-Golay smoothing filter methods could extract spectra information thoroughly. The correlation coefficient (r) of proanthocyanidins was 0.9621, SEC (st andard deviation of the calibration sets) was 0.64, and SEP (st andarddeviation of the prediction sets) was 0.94. The correlation coefficient (r) of total phenolics was 0.9254, SEC was 0.97, and SEP was 1.26. CONCLUSION: The near infrared diffuse reflectance spectroscopy method can be used to analyze the main active components in the seedpod of Nelumbo nucifera Gaertn rapidly, so it can be used routinely by the manufacturers for the quality control of the raw materials.
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OBJECTIVE: To establish a rapid method based on near-infrared diffuse reflectance spectroscopy (NIR) to monitor the blending process of traditional Chinese medicinal powder on-line. METHODS: NIR spectra were collected during the blending processes of mixtures consisting of Red Peony Root powder and defatted Spine Date Seed powder. Multivariate calibration models based on PLS regression were developed to correlate the collected spectra with the content of Red Peony Root powder. The optimal calibration model was applied to monitor the blending process in real time with noninterference. RESULTS: After spectral pretreatment using multiplicative signal correction (MSC), first derivative and Savitzky-Golay filter, Red Peony Root powder contents were quantified using PLS algorithm in the spectral ranges of 5900-5950 cm-1, 6700-6750 cm-1 and 6950-7100 cm-1. The correlation coefficient of the calibration model was 0.9990. The RMSEC, RMSEP and RMSECV were 1.14, 1.16 and 1.26, respectively. CONCLUSION: It was demonstrated that a miniature near-infrared analyzer could be used to monitor the contents of the constituents and the blending homogeneity of traditional Chinese medicinal powder in real time, and to rapidly determine the end-point of blending process. In addition, it can be used to judge whether the physical state of powder mixture conforms to the standard. Therefore, NIR spectroscopy is considered to be an appropriate PAT tool for end-point control of blending process of traditional Chinese medicinal powder.
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Con el objetivo de discriminar lesiones benignas y malignas en la piel humana a partir de espectros de reflexión difusa, se han analizado diferentes algoritmos de clasificación usando el software de aprendizaje automático y reconocimiento de patrones WEKA. Además, dada la alta dimensionalidad de la señal espectral, fue empleada una técnica selección de atributos para determinar las variables que aporten la mayor cantidad de información. Se probó la clasificación de la señal usando los algoritmos de máquinas de vectores de soporte, redes neuronales y bosques aleatorios, el desempeño fue evaluado usando el promedio de la k-fold cross-validation tomando en cuenta los porcentajes de instancias clasificadas correctamente, el índice kappa, el área bajo la curva ROC, la sensibilidad, y la especifidad. Finalmente se demuestra que el algoritmo de redes neuronales con los parámetros momentum y learning rate en 0,6 y 0,3 respectivamente, es el que mejor se adapta al problema de reconocimiento de patrones ya que clasifica correctamente al 89,89% de los casos.
In order to differentiate between benign and malignant lesions in the human skin using diffuse reflection spectra, different classification algorithms were tested using the WEKA data mining software. In addition, due to the high dimensionality of the spectral signal, an attribute selection technique was applied to determine the variables that contribute with more information. The spectral signal classification was tested using support vector machines, neural networks and random forests, their performance was measured using the k-fold cross-validation percentages of the Kappa statistic, area under the ROC curve, specificity and sensitivity. Finally it is shown that the one layer neural network with 6 neurons and the parameters momentum and learning rate in 0.6 and 0.3 respectively, is best suited to the problem of pattern recognition, achieving correctly classify 89.89% of the cases.
Subject(s)
Spectrum Analysis/statistics & numerical data , Spectrum Analysis/instrumentation , Spectrum Analysis/methods , Skin Neoplasms/diagnosis , Skin Neoplasms/prevention & control , Pattern Recognition, Automated , Neural Networks, ComputerABSTRACT
Object To establish a new method for the identification of Yangti (Chinese herb from Rumex L., Polygonaceae) by near infrared diffuse reflectance spectrometry. Methods Cluster analysis and discriminative analysis were adopted for their identification. Results The method can identify crude Yangti to a certain degree with results coincident with that of the traditional phytotoxnomy. Conclusion This method can be used for the rapid and accurate differentiation of crude drug of Rumex L..
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Objective To determine ecdysterone content in Radix Achyranthis Bidentalae by near-infrared diffuse reflectance spectroscopy (NIRDRS) combined with partial least squares (PLS). Methods NIRDRS and PLS. Results The correlation coefficient of the quantitative mathematics model between the prediction and the true values was 0.948 9. It is feasible to appling the above established method to determination of chemical constituents in Chinese materia medica. Conclusion Compared with other methods, the method is simple, rapid, high efficient, low expenditure, no pollution and with preparation undone and is suit for large quantity of unknown samples.
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AIM: To establish an identification method of Fritillaria based on near-infrared diffuse reflectance spectroscopy(NIRDRS). METHODS: Seven certified Fritillaria,i.e.,F.przewalskii Matim,F.cirrhosa D.Don,F.unibraacteate Hsiaaoet.K.C.Hsia,F.thunbergii Mig,F.pallidiflora,F.ussuriensis Matin and F.kupehensis Hsiaet K.C.Hsia,and three fake "Fritillaria",i.e.,F.thunbergii Varchekiugensis Hsiaet K.C.Hsia,Tulipa edulis and Iphigeniaindica were dried,grinded and sieved before their NIRDRS spectra were detected.Cluster analysis,convolution transform-visualization-similarity analysis were further employed to(identify) the NIRDRS of the ten herbal medicines. RESULTS: The zero-order NIRDRS spectra of the ten herbal medicines were too similar to be identified respectively.The cluster analysis helped differentiate the three fake "Fritillaria" from seven certified Fritillaria,but the identification between the certified Fritillaria remained dissatisfactory.The convolution transform-visualization-similarity analysis magnified and then quantified the minute differences between the certified Fritillaria,which significantly improved their identification. CONCLUSION: NIRDRS is a direct,non-destructive analytical method of solid samples.Coupled with information treatment techniques,DIRDRS provides a new identification method of crude traditional Chinese medicines.